{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "064c7557",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "aa66ae14",
   "metadata": {},
   "outputs": [],
   "source": [
    "stock_data=pd.read_csv(\"./stock_day.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "933f8154",
   "metadata": {},
   "outputs": [
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       "      <th>close</th>\n",
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       "      <th>volume</th>\n",
       "      <th>price_change</th>\n",
       "      <th>p_change</th>\n",
       "      <th>ma5</th>\n",
       "      <th>ma10</th>\n",
       "      <th>ma20</th>\n",
       "      <th>v_ma5</th>\n",
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       "    <tr>\n",
       "      <th>2018-02-27</th>\n",
       "      <td>23.53</td>\n",
       "      <td>25.88</td>\n",
       "      <td>24.16</td>\n",
       "      <td>23.53</td>\n",
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       "      <th>2018-02-26</th>\n",
       "      <td>22.80</td>\n",
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       "      <td>23.53</td>\n",
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       "      <td>22.942</td>\n",
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       "      <td>56007.50</td>\n",
       "      <td>1.53</td>\n",
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       "    <tr>\n",
       "      <th>2018-02-23</th>\n",
       "      <td>22.88</td>\n",
       "      <td>23.37</td>\n",
       "      <td>22.82</td>\n",
       "      <td>22.71</td>\n",
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       "      <td>0.54</td>\n",
       "      <td>2.42</td>\n",
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       "      <th>2018-02-22</th>\n",
       "      <td>22.25</td>\n",
       "      <td>22.76</td>\n",
       "      <td>22.28</td>\n",
       "      <td>22.02</td>\n",
       "      <td>36105.01</td>\n",
       "      <td>0.36</td>\n",
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       "      <td>21.909</td>\n",
       "      <td>23.137</td>\n",
       "      <td>35397.58</td>\n",
       "      <td>39904.78</td>\n",
       "      <td>60149.60</td>\n",
       "      <td>0.90</td>\n",
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       "    <tr>\n",
       "      <th>2018-02-14</th>\n",
       "      <td>21.49</td>\n",
       "      <td>21.99</td>\n",
       "      <td>21.92</td>\n",
       "      <td>21.48</td>\n",
       "      <td>23331.04</td>\n",
       "      <td>0.44</td>\n",
       "      <td>2.05</td>\n",
       "      <td>21.366</td>\n",
       "      <td>21.923</td>\n",
       "      <td>23.253</td>\n",
       "      <td>33590.21</td>\n",
       "      <td>42935.74</td>\n",
       "      <td>61716.11</td>\n",
       "      <td>0.58</td>\n",
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      "text/plain": [
       "             open   high  close    low    volume  price_change  p_change  \\\n",
       "2018-02-27  23.53  25.88  24.16  23.53  95578.03          0.63      2.68   \n",
       "2018-02-26  22.80  23.78  23.53  22.80  60985.11          0.69      3.02   \n",
       "2018-02-23  22.88  23.37  22.82  22.71  52914.01          0.54      2.42   \n",
       "2018-02-22  22.25  22.76  22.28  22.02  36105.01          0.36      1.64   \n",
       "2018-02-14  21.49  21.99  21.92  21.48  23331.04          0.44      2.05   \n",
       "\n",
       "               ma5    ma10    ma20     v_ma5    v_ma10    v_ma20  turnover  \n",
       "2018-02-27  22.942  22.142  22.875  53782.64  46738.65  55576.11      2.39  \n",
       "2018-02-26  22.406  21.955  22.942  40827.52  42736.34  56007.50      1.53  \n",
       "2018-02-23  21.938  21.929  23.022  35119.58  41871.97  56372.85      1.32  \n",
       "2018-02-22  21.446  21.909  23.137  35397.58  39904.78  60149.60      0.90  \n",
       "2018-02-14  21.366  21.923  23.253  33590.21  42935.74  61716.11      0.58  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dca75c21",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_drop=stock_data.drop([\"ma5\",\"ma10\",\"ma20\",\"v_ma5\",\"v_ma10\",\"v_ma20\"],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bdc361ca",
   "metadata": {},
   "outputs": [
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       "      <td>22.88</td>\n",
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       "      <td>22.82</td>\n",
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       "      <th>2015-03-06</th>\n",
       "      <td>13.17</td>\n",
       "      <td>14.48</td>\n",
       "      <td>14.28</td>\n",
       "      <td>13.13</td>\n",
       "      <td>179831.72</td>\n",
       "      <td>1.12</td>\n",
       "      <td>8.51</td>\n",
       "      <td>6.16</td>\n",
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       "      <th>2015-03-05</th>\n",
       "      <td>12.88</td>\n",
       "      <td>13.45</td>\n",
       "      <td>13.16</td>\n",
       "      <td>12.87</td>\n",
       "      <td>93180.39</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2.02</td>\n",
       "      <td>3.19</td>\n",
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       "      <th>2015-03-04</th>\n",
       "      <td>12.80</td>\n",
       "      <td>12.92</td>\n",
       "      <td>12.90</td>\n",
       "      <td>12.61</td>\n",
       "      <td>67075.44</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.57</td>\n",
       "      <td>2.30</td>\n",
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       "      <th>2015-03-03</th>\n",
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       "      <td>13.06</td>\n",
       "      <td>12.70</td>\n",
       "      <td>12.52</td>\n",
       "      <td>139071.61</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1.44</td>\n",
       "      <td>4.76</td>\n",
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       "      <th>2015-03-02</th>\n",
       "      <td>12.25</td>\n",
       "      <td>12.67</td>\n",
       "      <td>12.52</td>\n",
       "      <td>12.20</td>\n",
       "      <td>96291.73</td>\n",
       "      <td>0.32</td>\n",
       "      <td>2.62</td>\n",
       "      <td>3.30</td>\n",
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       "<p>643 rows × 8 columns</p>\n",
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       "             open   high  close    low     volume  price_change  p_change  \\\n",
       "2018-02-27  23.53  25.88  24.16  23.53   95578.03          0.63      2.68   \n",
       "2018-02-26  22.80  23.78  23.53  22.80   60985.11          0.69      3.02   \n",
       "2018-02-23  22.88  23.37  22.82  22.71   52914.01          0.54      2.42   \n",
       "2018-02-22  22.25  22.76  22.28  22.02   36105.01          0.36      1.64   \n",
       "2018-02-14  21.49  21.99  21.92  21.48   23331.04          0.44      2.05   \n",
       "...           ...    ...    ...    ...        ...           ...       ...   \n",
       "2015-03-06  13.17  14.48  14.28  13.13  179831.72          1.12      8.51   \n",
       "2015-03-05  12.88  13.45  13.16  12.87   93180.39          0.26      2.02   \n",
       "2015-03-04  12.80  12.92  12.90  12.61   67075.44          0.20      1.57   \n",
       "2015-03-03  12.52  13.06  12.70  12.52  139071.61          0.18      1.44   \n",
       "2015-03-02  12.25  12.67  12.52  12.20   96291.73          0.32      2.62   \n",
       "\n",
       "            turnover  \n",
       "2018-02-27      2.39  \n",
       "2018-02-26      1.53  \n",
       "2018-02-23      1.32  \n",
       "2018-02-22      0.90  \n",
       "2018-02-14      0.58  \n",
       "...              ...  \n",
       "2015-03-06      6.16  \n",
       "2015-03-05      3.19  \n",
       "2015-03-04      2.30  \n",
       "2015-03-03      4.76  \n",
       "2015-03-02      3.30  \n",
       "\n",
       "[643 rows x 8 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "data_drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "43efc2d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23.53"
      ]
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "data_drop[\"open\"][\"2018-02-27\"]"
   ]
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  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a9554503",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018-02-27    25.88\n",
       "2018-02-26    23.78\n",
       "2018-02-23    23.37\n",
       "Name: high, dtype: float64"
      ]
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     "execution_count": 7,
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    "data_drop.loc[\"2018-02-27\":\"2018-02-23\",\"high\"]"
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  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a6ef4cec",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "             open   high  close    low    volume\n",
       "2018-02-27  23.53  25.88  24.16  23.53  95578.03\n",
       "2018-02-26  22.80  23.78  23.53  22.80  60985.11\n",
       "2018-02-23  22.88  23.37  22.82  22.71  52914.01"
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  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7a63eb2e",
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": ".iloc requires numeric indexers, got ['high' 'close']",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32mC:\\Users\\JUSTWA~1\\AppData\\Local\\Temp/ipykernel_3444/3155863765.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdata_drop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"high\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m\"close\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mc:\\users\\justwatch\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    923\u001b[0m                 \u001b[1;32mwith\u001b[0m \u001b[0msuppress\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    924\u001b[0m                     \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtakeable\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_takeable\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 925\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_tuple\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    926\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    927\u001b[0m             \u001b[1;31m# we by definition only have the 0th axis\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\justwatch\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[1;34m(self, tup)\u001b[0m\n\u001b[0;32m   1504\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mtuple\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1505\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1506\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_valid_tuple\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1507\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0msuppress\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mIndexingError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1508\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_lowerdim\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\justwatch\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_has_valid_tuple\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    752\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mk\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    753\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 754\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    755\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    756\u001b[0m                 raise ValueError(\n",
      "\u001b[1;32mc:\\users\\justwatch\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_validate_key\u001b[1;34m(self, key, axis)\u001b[0m\n\u001b[0;32m   1418\u001b[0m             \u001b[1;31m# check that the key has a numeric dtype\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1419\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mis_numeric_dtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1420\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\".iloc requires numeric indexers, got {arr}\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1421\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1422\u001b[0m             \u001b[1;31m# check that the key does not exceed the maximum size of the index\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIndexError\u001b[0m: .iloc requires numeric indexers, got ['high' 'close']"
     ]
    }
   ],
   "source": [
    "data_drop.iloc[:5,[\"high\",\"close\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "549c70c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>close</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>price_change</th>\n",
       "      <th>p_change</th>\n",
       "      <th>turnover</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-02-27</th>\n",
       "      <td>23.53</td>\n",
       "      <td>25.88</td>\n",
       "      <td>24.16</td>\n",
       "      <td>23.53</td>\n",
       "      <td>95578.03</td>\n",
       "      <td>0.63</td>\n",
       "      <td>2.68</td>\n",
       "      <td>2.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-26</th>\n",
       "      <td>22.80</td>\n",
       "      <td>23.78</td>\n",
       "      <td>23.53</td>\n",
       "      <td>22.80</td>\n",
       "      <td>60985.11</td>\n",
       "      <td>0.69</td>\n",
       "      <td>3.02</td>\n",
       "      <td>1.53</td>\n",
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       "    <tr>\n",
       "      <th>2018-02-23</th>\n",
       "      <td>22.88</td>\n",
       "      <td>23.37</td>\n",
       "      <td>22.82</td>\n",
       "      <td>22.71</td>\n",
       "      <td>52914.01</td>\n",
       "      <td>0.54</td>\n",
       "      <td>2.42</td>\n",
       "      <td>1.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-22</th>\n",
       "      <td>22.25</td>\n",
       "      <td>22.76</td>\n",
       "      <td>22.28</td>\n",
       "      <td>22.02</td>\n",
       "      <td>36105.01</td>\n",
       "      <td>0.36</td>\n",
       "      <td>1.64</td>\n",
       "      <td>0.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-14</th>\n",
       "      <td>21.49</td>\n",
       "      <td>21.99</td>\n",
       "      <td>21.92</td>\n",
       "      <td>21.48</td>\n",
       "      <td>23331.04</td>\n",
       "      <td>0.44</td>\n",
       "      <td>2.05</td>\n",
       "      <td>0.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2015-03-06</th>\n",
       "      <td>13.17</td>\n",
       "      <td>14.48</td>\n",
       "      <td>14.28</td>\n",
       "      <td>13.13</td>\n",
       "      <td>179831.72</td>\n",
       "      <td>1.12</td>\n",
       "      <td>8.51</td>\n",
       "      <td>6.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-05</th>\n",
       "      <td>12.88</td>\n",
       "      <td>13.45</td>\n",
       "      <td>13.16</td>\n",
       "      <td>12.87</td>\n",
       "      <td>93180.39</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2.02</td>\n",
       "      <td>3.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-04</th>\n",
       "      <td>12.80</td>\n",
       "      <td>12.92</td>\n",
       "      <td>12.90</td>\n",
       "      <td>12.61</td>\n",
       "      <td>67075.44</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.57</td>\n",
       "      <td>2.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-03</th>\n",
       "      <td>12.52</td>\n",
       "      <td>13.06</td>\n",
       "      <td>12.70</td>\n",
       "      <td>12.52</td>\n",
       "      <td>139071.61</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1.44</td>\n",
       "      <td>4.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-02</th>\n",
       "      <td>12.25</td>\n",
       "      <td>12.67</td>\n",
       "      <td>12.52</td>\n",
       "      <td>12.20</td>\n",
       "      <td>96291.73</td>\n",
       "      <td>0.32</td>\n",
       "      <td>2.62</td>\n",
       "      <td>3.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>643 rows × 8 columns</p>\n",
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      ],
      "text/plain": [
       "             open   high  close    low     volume  price_change  p_change  \\\n",
       "2018-02-27  23.53  25.88  24.16  23.53   95578.03          0.63      2.68   \n",
       "2018-02-26  22.80  23.78  23.53  22.80   60985.11          0.69      3.02   \n",
       "2018-02-23  22.88  23.37  22.82  22.71   52914.01          0.54      2.42   \n",
       "2018-02-22  22.25  22.76  22.28  22.02   36105.01          0.36      1.64   \n",
       "2018-02-14  21.49  21.99  21.92  21.48   23331.04          0.44      2.05   \n",
       "...           ...    ...    ...    ...        ...           ...       ...   \n",
       "2015-03-06  13.17  14.48  14.28  13.13  179831.72          1.12      8.51   \n",
       "2015-03-05  12.88  13.45  13.16  12.87   93180.39          0.26      2.02   \n",
       "2015-03-04  12.80  12.92  12.90  12.61   67075.44          0.20      1.57   \n",
       "2015-03-03  12.52  13.06  12.70  12.52  139071.61          0.18      1.44   \n",
       "2015-03-02  12.25  12.67  12.52  12.20   96291.73          0.32      2.62   \n",
       "\n",
       "            turnover  \n",
       "2018-02-27      2.39  \n",
       "2018-02-26      1.53  \n",
       "2018-02-23      1.32  \n",
       "2018-02-22      0.90  \n",
       "2018-02-14      0.58  \n",
       "...              ...  \n",
       "2015-03-06      6.16  \n",
       "2015-03-05      3.19  \n",
       "2015-03-04      2.30  \n",
       "2015-03-03      4.76  \n",
       "2015-03-02      3.30  \n",
       "\n",
       "[643 rows x 8 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "aa64f7d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_drop.close=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ff38314b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>2018-02-27</th>\n",
       "      <td>23.53</td>\n",
       "      <td>25.88</td>\n",
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       "      <td>23.53</td>\n",
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       "      <td>2.39</td>\n",
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       "      <th>2018-02-26</th>\n",
       "      <td>22.80</td>\n",
       "      <td>23.78</td>\n",
       "      <td>1</td>\n",
       "      <td>22.80</td>\n",
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       "      <td>3.02</td>\n",
       "      <td>1.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-23</th>\n",
       "      <td>22.88</td>\n",
       "      <td>23.37</td>\n",
       "      <td>1</td>\n",
       "      <td>22.71</td>\n",
       "      <td>52914.01</td>\n",
       "      <td>0.54</td>\n",
       "      <td>2.42</td>\n",
       "      <td>1.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-22</th>\n",
       "      <td>22.25</td>\n",
       "      <td>22.76</td>\n",
       "      <td>1</td>\n",
       "      <td>22.02</td>\n",
       "      <td>36105.01</td>\n",
       "      <td>0.36</td>\n",
       "      <td>1.64</td>\n",
       "      <td>0.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-14</th>\n",
       "      <td>21.49</td>\n",
       "      <td>21.99</td>\n",
       "      <td>1</td>\n",
       "      <td>21.48</td>\n",
       "      <td>23331.04</td>\n",
       "      <td>0.44</td>\n",
       "      <td>2.05</td>\n",
       "      <td>0.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-06</th>\n",
       "      <td>13.17</td>\n",
       "      <td>14.48</td>\n",
       "      <td>1</td>\n",
       "      <td>13.13</td>\n",
       "      <td>179831.72</td>\n",
       "      <td>1.12</td>\n",
       "      <td>8.51</td>\n",
       "      <td>6.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-05</th>\n",
       "      <td>12.88</td>\n",
       "      <td>13.45</td>\n",
       "      <td>1</td>\n",
       "      <td>12.87</td>\n",
       "      <td>93180.39</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2.02</td>\n",
       "      <td>3.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-04</th>\n",
       "      <td>12.80</td>\n",
       "      <td>12.92</td>\n",
       "      <td>1</td>\n",
       "      <td>12.61</td>\n",
       "      <td>67075.44</td>\n",
       "      <td>0.20</td>\n",
       "      <td>1.57</td>\n",
       "      <td>2.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-03</th>\n",
       "      <td>12.52</td>\n",
       "      <td>13.06</td>\n",
       "      <td>1</td>\n",
       "      <td>12.52</td>\n",
       "      <td>139071.61</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1.44</td>\n",
       "      <td>4.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-02</th>\n",
       "      <td>12.25</td>\n",
       "      <td>12.67</td>\n",
       "      <td>1</td>\n",
       "      <td>12.20</td>\n",
       "      <td>96291.73</td>\n",
       "      <td>0.32</td>\n",
       "      <td>2.62</td>\n",
       "      <td>3.30</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>643 rows × 8 columns</p>\n",
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      "text/plain": [
       "             open   high  close    low     volume  price_change  p_change  \\\n",
       "2018-02-27  23.53  25.88      1  23.53   95578.03          0.63      2.68   \n",
       "2018-02-26  22.80  23.78      1  22.80   60985.11          0.69      3.02   \n",
       "2018-02-23  22.88  23.37      1  22.71   52914.01          0.54      2.42   \n",
       "2018-02-22  22.25  22.76      1  22.02   36105.01          0.36      1.64   \n",
       "2018-02-14  21.49  21.99      1  21.48   23331.04          0.44      2.05   \n",
       "...           ...    ...    ...    ...        ...           ...       ...   \n",
       "2015-03-06  13.17  14.48      1  13.13  179831.72          1.12      8.51   \n",
       "2015-03-05  12.88  13.45      1  12.87   93180.39          0.26      2.02   \n",
       "2015-03-04  12.80  12.92      1  12.61   67075.44          0.20      1.57   \n",
       "2015-03-03  12.52  13.06      1  12.52  139071.61          0.18      1.44   \n",
       "2015-03-02  12.25  12.67      1  12.20   96291.73          0.32      2.62   \n",
       "\n",
       "            turnover  \n",
       "2018-02-27      2.39  \n",
       "2018-02-26      1.53  \n",
       "2018-02-23      1.32  \n",
       "2018-02-22      0.90  \n",
       "2018-02-14      0.58  \n",
       "...              ...  \n",
       "2015-03-06      6.16  \n",
       "2015-03-05      3.19  \n",
       "2015-03-04      2.30  \n",
       "2015-03-03      4.76  \n",
       "2015-03-02      3.30  \n",
       "\n",
       "[643 rows x 8 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "data_drop"
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  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bf57e230",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data_drop.sort_values(by=\"open\",ascending=True)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "21d739e7",
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   "outputs": [
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       "      <th>2015-03-02</th>\n",
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       "      <th>2015-03-04</th>\n",
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       "      <th>2015-03-05</th>\n",
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       "      <td>13.45</td>\n",
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       "      <td>12.87</td>\n",
       "      <td>93180.39</td>\n",
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       "      <td>1.59</td>\n",
       "      <td>5.92</td>\n",
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       "    <tr>\n",
       "      <th>2017-11-01</th>\n",
       "      <td>33.85</td>\n",
       "      <td>34.34</td>\n",
       "      <td>1</td>\n",
       "      <td>33.10</td>\n",
       "      <td>232325.30</td>\n",
       "      <td>-0.61</td>\n",
       "      <td>-1.77</td>\n",
       "      <td>5.81</td>\n",
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       "      <th>2015-06-10</th>\n",
       "      <td>34.10</td>\n",
       "      <td>36.35</td>\n",
       "      <td>1</td>\n",
       "      <td>32.23</td>\n",
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       "      <td>1.53</td>\n",
       "      <td>9.21</td>\n",
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       "      <th>2015-06-12</th>\n",
       "      <td>34.69</td>\n",
       "      <td>35.98</td>\n",
       "      <td>1</td>\n",
       "      <td>34.01</td>\n",
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       "      <td>5.47</td>\n",
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       "      <th>2015-06-15</th>\n",
       "      <td>34.99</td>\n",
       "      <td>34.99</td>\n",
       "      <td>1</td>\n",
       "      <td>31.69</td>\n",
       "      <td>199369.53</td>\n",
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       "             open   high  close    low     volume  price_change  p_change  \\\n",
       "2015-03-02  12.25  12.67      1  12.20   96291.73          0.32      2.62   \n",
       "2015-09-02  12.30  14.11      1  12.30   70201.74         -1.10     -8.17   \n",
       "2015-03-03  12.52  13.06      1  12.52  139071.61          0.18      1.44   \n",
       "2015-03-04  12.80  12.92      1  12.61   67075.44          0.20      1.57   \n",
       "2015-03-05  12.88  13.45      1  12.87   93180.39          0.26      2.02   \n",
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       "2015-06-11  33.17  34.98      1  32.51  173075.73          0.54      1.59   \n",
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       "2015-06-12  34.69  35.98      1  34.01  159825.88          0.82      2.38   \n",
       "2015-06-15  34.99  34.99      1  31.69  199369.53         -3.52    -10.00   \n",
       "\n",
       "            turnover  \n",
       "2015-03-02      3.30  \n",
       "2015-09-02      2.40  \n",
       "2015-03-03      4.76  \n",
       "2015-03-04      2.30  \n",
       "2015-03-05      3.19  \n",
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       "2015-06-11      5.92  \n",
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       "2015-06-10      9.21  \n",
       "2015-06-12      5.47  \n",
       "2015-06-15      6.82  \n",
       "\n",
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   "id": "a6228804",
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   "outputs": [
    {
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       "      <td>12.61</td>\n",
       "      <td>67075.44</td>\n",
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       "      <td>1.57</td>\n",
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       "      <td>1.44</td>\n",
       "      <td>4.76</td>\n",
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       "      <th>2015-09-02</th>\n",
       "      <td>12.30</td>\n",
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       "      <td>1</td>\n",
       "      <td>12.30</td>\n",
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       "      <td>-8.17</td>\n",
       "      <td>2.40</td>\n",
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       "      <th>2015-03-02</th>\n",
       "      <td>12.25</td>\n",
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       "             open   high  close    low     volume  price_change  p_change  \\\n",
       "2015-06-15  34.99  34.99      1  31.69  199369.53         -3.52    -10.00   \n",
       "2015-06-12  34.69  35.98      1  34.01  159825.88          0.82      2.38   \n",
       "2015-06-10  34.10  36.35      1  32.23  269033.12          0.51      1.53   \n",
       "2017-11-01  33.85  34.34      1  33.10  232325.30         -0.61     -1.77   \n",
       "2015-06-11  33.17  34.98      1  32.51  173075.73          0.54      1.59   \n",
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       "2015-03-03  12.52  13.06      1  12.52  139071.61          0.18      1.44   \n",
       "2015-09-02  12.30  14.11      1  12.30   70201.74         -1.10     -8.17   \n",
       "2015-03-02  12.25  12.67      1  12.20   96291.73          0.32      2.62   \n",
       "\n",
       "            turnover  \n",
       "2015-06-15      6.82  \n",
       "2015-06-12      5.47  \n",
       "2015-06-10      9.21  \n",
       "2017-11-01      5.81  \n",
       "2015-06-11      5.92  \n",
       "...              ...  \n",
       "2015-03-05      3.19  \n",
       "2015-03-04      2.30  \n",
       "2015-03-03      4.76  \n",
       "2015-09-02      2.40  \n",
       "2015-03-02      3.30  \n",
       "\n",
       "[643 rows x 8 columns]"
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     "execution_count": 14,
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   "execution_count": null,
   "id": "c6eac0ee",
   "metadata": {},
   "outputs": [],
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